In imaging contexts, color reproduction and accuracy is an important feature in image quality and appearance. For example, color errors caused during color conversion may reduce image quality and appearance for end users. In some examples, such color errors may be caused by the limited color space range of an image sensor and/or quantization. Furthermore, such color errors may be caused in the color matching between devices (e.g., a device link). Such color errors may be dependent on image signal processing and/or the calibration of color-conversion of the image signal processing.
It may be desirable to limit or eliminate such color errors and to reproduce a natural or user-preference based image appearance on various displays and/or printed materials with minimal color error. Current color mapping techniques may include single color correction matrix (CCM) color conversion, 1-dimensional (1D) look-up-table (e.g., Gamma Curve) color conversion, or 3D look-up-table in red green blue (RGB)/cyan yellow magenta key or black (CYMK) color space color conversion. However, such techniques suffer problems or limitations such as limitations in accuracy, difficulty or computational complexity in implementation, variance to gain/exposure variations, and the like.
It may be advantageous to perform such color mapping with greater accuracy and/or with less computational requirements. It is with respect to these and other considerations that the present improvements have been needed. Such improvements may become critical as the desire to provide high quality images, to provide better robustness, and to reach any requested color appearance become more widespread.